This course has two foundational goals: (1) to develop core skills in “data management,” which are important regardless of which programming language you use, and (2) to learn the fundamentals of the R programming language.
Data management consists of acquiring, investigating, cleaning, combining, and manipulating data. Most statistics courses teach you how to analyze data that are ready for analysis. In real research projects, cleaning the data and creating analysis datasets is often more time consuming than conducting analyses. This course teaches the fundamental data management and data manipulation skills necessary for creating analysis datasets.
The course will be taught in R, a free, open-source programming language. R has become the most popular language for statistical analysis, surpassing SPSS, Stata, and SAS. What differentiates R from these other languages is the thousands of open-source “libraries” created by R users. R is one of the most popular languages for “data science” because R libraries have been created for web-scraping, mapping, network analysis, etc. By learning R you can be confident that you know a programming language that can run any modeling technique you might need and has amazing capabilities for data collection and data visualization. By learning fundamentals of R in this course, you will be “one step away” from web-scraping, network analysis, interactive maps, quantitative text analysis, or whatever other data science application you are interested in.
| Resource | Link |
|---|---|
| Class website | https://anyone-can-cook.github.io/rclass1/ |
| Class zoom link | https://ucla.zoom.us/j/94774035711 |
| Questions & Discussion | https://github.com/anyone-can-cook/rclass1_student_issues |
| Announcements | https://github.com/orgs/anyone-can-cook/teams/rclass1_announcements |
Ozan Jaquette
Patricia Martín
Crystal Han
For the first two weeks of the course, we will have synchronous lectures and class time will be on Fridays from 8:30am to 11:20am. In the subsequent weeks, we will have asynchronous (pre-class) lectures and a synchronous workshop-style class that meets on Fridays from 10am to 11:20am. Weekly homework will consist of students working through the lectures on their own, a modest amount of required reading, and weekly problem sets completed in groups of three.
We all have a responsibility to ensure that every member of the class feels valued and safe. Be mindful that our words and body language affects others in ways we might not fully understand. We have a responsibility to express our ideas in a way that doesn’t make disparaging generalizations and doesn’t make people feel excluded. As an instructor, I am responsible for setting an example through my own conduct.
Learning data management, while trying to get a handle on R and unfamiliar, data can feel overwhelming! We must create an environment where students feel comfortable asking questions and talking about what they did not understand. Discomfort is part of the learning process. Unburdern yourself from the weight of being an “expert.” Focus your energy on improving and helping your classmates improve.
This course teaches data management and R programming, tools that are often percieved as objective, independent of context and content. We must acknowledge that racism, white supremacy, and heteronormative ideas of gender identity and sexual orientation are are rooted in every aspect of data. These seemingly objective rules (e.g., “the right way to handle data”) affect the way data are gathered, how variables are created, the questions asked (or not asked), etc.
In this course we will utilize data that reflect systemic gaps based on race, ethnicity, immigration status, and gender identity, among other aspects of identity. It is critical to acknowledge that the processes used to create these datadata (e.g., how data collected, the categories chosen to represent identity) are often based on notions of white supremacy and heteronormativity. When you encounter a data management strategy that that may cause harm, we encourage you to raise concerns. It maybe that your instructor/TAs may need to think more critically about strategies they have been using for a long time! It is also critical that we acknowledge that the social and economic marginalization reflected in data is rooted in systemic oppression that upholds white supremacy and heteronormativity. We should all be reflecting about our own role in upholding these systems.
EDUC 263: Intro to Programming & Data Management Using R Time: Fridays 08:30 AM Pacific Time (US and Canada) (*Only for the first two weeks)
Join Zoom Meeting
All course related material can be found on the course website. Pre-recorded lecture videos, lecture slides (PDF/HTML), and .Rmd files will be posted on the class website under the associated sections. Additional resources (e.g., syllabus) may also be posted on the class website.
We will be using GitHub teams for class announcements HERE.
GitHub teams: The teaching team will post all class announcements using GitHub teams. The GitHub team discussions feature allows for quick and seamless communication to all members of an organization or team – in this case, to all students with a GitHub account enrolled in the course. Some features include:
@mentioned by all students enrolled in the class and part of the organization.Credit: Introducing team discussions
We will be using GitHub issues for questions and class discussion HERE.
GitHub issues: GitHub issues are traditionally used by collaborators of a repository for managing tasks for a project. Our rational for using issues is twofold: 1) help track and organize questions related to course material and problem sets and 2) promote classroom participation. Students are encouraged to contribute to issues by posting questions, sharing helpful resources, and/or taking a stab at answering questions posted on issues. Some features include:
If you have a personal question or issue, you can email the instructor or TA directly. Additionally, we are available for office hours or by appointment if there is anything you would like to discuss with us in private.
Course readings will be assigned from:
Required software we will be using:
Course grade will be based on the following components:
Students will complete 10 problem sets (the last one due during finals week). Problem sets are due by 10am each Friday, right before we start class.
Late submissions will lose 20% (i.e., max grade becomes 80%). Problem sets not submitted by 12pm the following Monday will not receive points because at that point we will post solutions on the course website. The lowest problem-set grade will be dropped from the calculation of your final grade.
Your will not lose points for late submission if you cannot submit a problem set due to an unexpected emergency. But please contact the instructor by email as soon as you can so we can work out a plan.
In general, each problem set will give you practice using the skills and concepts introduced during the previous lecture. For example, after the lecture on joining (merging) datasets, the problem set for that week will require that students complete several different tasks involving merging data. Additionally, the weekly problem sets will require you to use data manipulation skills you learned in previous weeks.
With the exception of the first problem set, students will complete problem sets in groups of 3. We will form groups during class in week 2 and you will keep the same group throughout the quarter. However, each student will submit their own assignment. You are encouraged to work together and get help from your group. However, it is important that you understand how to do the problem set on your own, rather than copying the solution developed by group members.
Since you will be working together, it is understandable that answers for many questions will be the same as your group members. However, if I find compelling evidence that a student merely copied solutions from a classmate, I will consider this a violation of academic integrity and that student will receive a zero for the homework assignment.
A general strategy I recommend for completing the problem sets is as follows: (1) after lecture, do the reading associated with that lecture; (2) try doing the problem set on your own; (3) communicate with your group to work through the problem set, with a particular focus on areas group members find challenging.
Link to problem set expectations and helpful resources HERE.
Students are expected to participate in the weekly class meetings by being attentive, supportive, by asking questions, or by answering questions posed by others on Zoom. Additionally, students can receive strong participation grades by asking questions and answering questions on GitHub issues.
Students are required to attend the weekly class meetings (unless you have talked to the instructors about this beforehand). Each unexcused absence results in a loss of 20% from your attendance/participation grade. Three or more unexcused absences will result in a failing grade for the course.
An excused absence is a professional opportunity that you discuss with me beforehand or a medical, or family emergency. Excused absences will not result in a loss of attendance points. However, you will be responsible for all material covered in that class and you will be expected to turn in homework assignments on time.
| Letter Grade | Percentage |
|---|---|
| A+ | 99-100% |
| A | 93<99% |
| A- | 90<93% |
| B+ | 87<90% |
| B | 83<87% |
| B- | 80<83% |
| C+ | 77<80% |
| C | 73<77% |
| C- | 70<73% |
| D | 60<70% |
| F | 0<60% |
With the ongoing spread of the COVID-19 pandemic, we understand that right now is a challenging time for everybody. Many of us may be experiencing added stress or responsibilties that make learning and completing classwork difficult. If you are having trouble keeping up with the class, please reach out to the teaching team and we will help work out a plan with you. We understand that right now is a precarious time and in the event that you or someone in your family and/or shared living space gets sick, we ask that you please reach out to us as soon as you are able to. We want to be accomodating to everyone’s unique situation and hope to make this class an enjoyable learning experience for all.
You will communicate with instructors and peers virtually through a variety of tools such as GitHub, email, and Zoom web conferencing. The following guidelines will enable everyone in the course to participate and collaborate in a productive, safe environment.
Class Zoom guidelines
All synchronous class sessions will be held online, via Zoom. Below, we have outlined some general guidelines about Zoom learning. As we continue learning together, we can add to and change the below list. I’m open to your feedback and your experiences as we continue to learn how to learn via Zoom.
Center for Accessible Education
Students needing academic accommodations based on a disability should contact the Center for Accessible Education (CAE). When possible, students should contact the CAE within the first two weeks of the term as reasonable notice is needed to coordinate accommodations. For more information visit https://www.cae.ucla.edu/.
Located in A255 Murphy Hall: (310) 825-1501, TDD (310) 206-6083; http://www.cae.ucla.edu/
UCLA policy
This class
Below is an overview of the tentative course schedule, which is subject to change at the discretion of the instructor. Topics may be cut if we need to devote more time to learning the most central topics. It is unlikely that additional topics will be added. The official course schedule, required reading, and optional reading will be posted on the course website.
As a student you may experience a range of issues that can cause barriers to learning, such as strained relationships, increased anxiety, alcohol/drug problems, depression, difficulty concentrating and/or lack of motivation. These mental health concerns or stressful events may lead to diminished academic performance or reduce a student’s ability to participate in daily activities. UC offers services to assist you with addressing these and other concerns you may be experiencing. If you or someone you know are suffering from any of the aforementioned conditions, consider utilizing the confidential mental health services available on campus.
Students in distress may speak directly with a counselor 24/7 at (310) 825-0768, or may call 911; located in Wooden Center West; https://www.caps.ucla.edu
UCLA is committed to maintaining a campus community that provides the stronget possible support for the intellectual and personal growth of all its members- students, faculty, and staff. Acts intended to create a hostile climate are unacceptable.
The LGBTQ resource center provides a range of education and advocacy services supporting intersectional identity development. It fosters unity; wellness; and an open, safe, inclusive environment for lesbian, gay, bisexual, intersex, transgender, queer, asexual, questioning, and same-gender-loving students, their families, and the entire campus community. Find it in the Student Activities Center, or via email lgbt@lgbt.ucla.edu.
The Dashew Center provides a range of programs to promote cross-cultural learning, language improvement, and cultural adjustment. Their programs include trips in the LA area, performances, and on-campus events and workshops.
This program provides a safe space for undergraduate and graduate undocument students. USP supports the UndocuBruin community through personalized services and resources, programs, and workshops.
UCLA Student Legal Services provides a range of legal support to all registered and enrolled UCLA students. Some of their services include:
Due to COVID, Student legal Services is closed to walk-ins.
UCLA Students with Dependents provides support to UCLA studens who are parents, guardians, and caregivers. Some of their services include:
For more information visit their website: https://www.swd.ucla.edu/
Lactation Rooms
Gender Inclusive restrooms
Campus accessibility
Title IX prohibits gender discrimination, including sexual harassment, domestic and dating violence, sexual assault, and stalking. If you have experienced sexual harassment or sexual violence, there are a variety of resources to assist you.
CONFIDENTIAL RESOURCES:You can receive confidential support and advocacy at the CARE Advocacy Office for Sexual and Gender-Based Violence, A233 Murphy Hall, CAREadvocate@careprogram.ucla.edu, (310) 206-2465. Counseling and Psychological Services (CAPS) also provides confidential counseling to all students and can be reached 24/7 at (310) 825-0768.
NON-CONFIDENTIAL RESOURCES: You can also report sexual violence or sexual harassment directly to the University’s Title IX Coordinator, 2255 Murphy Hall, titleix@conet.ucla.edu, (310) 206-3417. Reports to law enforcement can be made to UCPD at (310) 825-1491. These offices may be required to pursue an official investigation.
Faculty and TAs are required under the UC Policy on Sexual Violence and Sexual Harassment to inform the Title IX Coordinator should they become aware that you or any other student has experienced sexual violence or sexual harassment.